000			01557nab a2200253 c 4500
999			_c145833 _d145833
003			ES-MaIEF
005			20220509172601.0
007			ta
008			220509t2021 us ||||| |||| 00| 0|eng d
040			_aES-MaIEF _bspa _cES-MaIEF
100			_955949 _aHeitzman, Shane M.
245		0	_aTax loss measurement _c Shane Heitzman and Rebecca Lester
500			_aResumen.
504			_aBibliografía.
520			_aWe use financial disclosures to develop a novel proxy for net operating loss carryforward (NOL) tax benefits. This approach more accurately identifies firms with tax losses, more precisely measures the tax loss, and better predicts reductions in future taxes than existing proxies. We derive a prediction model, which future researchers can employ to better approximate the NOL tax benefits based on readily available financial data. We also demonstrate how NOL nonlinearity affects measurement of corporate tax status. By proposing a new measure and demonstrating trade-offs across competing proxies, we contribute to the work in public economics, corporate finance, and tax accounting that examines the responsiveness of the business sector to corporate tax incentives.
650			_aSOCIEDADES _948454
650			_aIMPUESTOS _947460
650			_aGASTOS FISCALES _950212
650			_aINCENTIVOS FISCALES _947462
650		4	_947776 _aMODELOS ECONOMETRICOS
700			_964762 _aLester, Rebecca
773	0		_9167132 _oOP 233/2021/4 _tNational Tax Journal _w(IEF)86491 _x 0028-0283 _g v. 74, n. 4, December 2021, p. 867–893
942			_cART